File "./MELM-master/tools/../lib/nets/network.py", line 384, in get_refine_supervision roi_weights[:, 0] = max_box_score[gt_assignment, 0] ValueError: could not broadcast input array from shape (761) into shape (500)

[nawang0226]

Hi, following the ReadMe, whatever it just doesn't work and I don't know how to fix it. The problem is

• voc_2007_trainval ss roidb loaded from /data3/CV_WN/MELM-master/data/cache/voc_2007_trainval_selective_search_roidb.pkl done Preparing training data... done 10022 roidb entries Output will be saved to /data3/CV_WN/MELM-master/output/vgg16/voc_2007_trainval/default TensorFlow summaries will be saved to /data3/CV_WN/MELM-master/tensorboard/vgg16/voc_2007_trainval/default Loaded dataset voc_2007_test for training Set proposal method: selective_search Preparing training data... voc_2007_test ss roidb loaded from /data3/CV_WN/MELM-master/data/cache/voc_2007_test_selective_search_roidb.pkl done 4952 validation roidb entries Filtered 0 roidb entries: 10022 -> 10022 Filtered 0 roidb entries: 4952 -> 4952 Solving... Loading initial model weights from data/imagenet_weights/vgg16.pth Loaded. Traceback (most recent call last): File "./tools/trainval_net.py", line 130, in max_iters=args.max_iters) File "/data3/CV_WN/MELM-master/tools/../lib/model/train_val.py", line 357, in train_net sw.train_model(max_iters) File "/data3/CV_WN/MELM-master/tools/../lib/model/train_val.py", line 265, in train_model self.net.train_step_with_summary(blobs, self.optimizer) File "/data3/CV_WN/MELM-master/tools/../lib/nets/network.py", line 727, in train_step_with_summary self.forward(blobs['data'], blobs['image_level_labels'],blobs['im_info'], blobs['gt_boxes'], blobs['ss_boxes']) File "/data3/CV_WN/MELM-master/tools/../lib/nets/network.py", line 633, in forward self._add_losses() # compute losses File "/data3/CV_WN/MELM-master/tools/../lib/nets/network.py", line 250, in _add_losses self._image_gt_summaries['image_level_label']) File "/data3/CV_WN/MELM-master/tools/../lib/nets/network.py", line 384, in get_refine_supervision roi_weights[:, 0] = max_box_score[gt_assignment, 0] ValueError: could not broadcast input array from shape (761) into shape (500)

Thanks for all have you done and look forward to your early reply to this problem.

[zwy1996]

Hi, I met the same error, did you handle it?

[nawang0226]

no, haven't handle it.

[vasgaowei]

I am sorry, last week I made a update for supporting varied numbers of ROIs for forward operations in case of not enough GPU memory. And you can fix the bugs as following: in network.py file, in _add_losses functions, in lines 244, change to self.get_refine_supervision(det_cls_product, self._image_gt_summaries['ss_boxes'][self.ss_boxes_indexes ,:],self._image_gt_summaries['image_level_label']). And for line 257 do the same operation. And I will fix this small bugs soon.